Abstract :
The author considers recursive identification of time-varying systems having finite impulse response, focusing on the tradeoff between tracking capability and disturbance rejection. Approximate, but simple and explicit, frequency-domain expressions for the model quality are derived for three different identification algorithms. The results, derived under the assumption of slow adaptation, slow system variation, and high model order, are extensions of the results presented by Gunnarsson and Ljung (see ibid., vol.37, p.1072, 1989) to the case where the system output is affected by correlated disturbances
Keywords :
approximation theory; identification; signal processing; time-varying systems; tracking; approximate expressions; correlated disturbances; disturbance rejection; finite impulse response; frequency-domain expressions; high model order; identification algorithms; model quality; recursively identified FIR models; slow adaptation; slow system variation; system output; time-varying systems; tracking; Bars; Colored noise; Finite impulse response filter; Geology; Geophysics computing; Recursive estimation; Signal processing; Time varying systems; Vectors; White noise;